数据挖掘技术系统综述

Robert Hoehndor
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引用次数: 0

摘要

数据挖掘是在庞大而复杂的数据集中揭示设计和示例。有两种类型的数据挖掘:模型结构和示例位置。数据挖掘中的模型结构非常类似于事实证明,尽管由于数据索引的巨大规模以及数据挖掘通常是可选信息检查的方式而出现了新的问题。例子发现在信息中寻找特殊性或小的邻近设计,而大量的信息是不重要的。当然,对大量大规模信息挖掘练习的一种看法是,它们基本上包括分离和数据简化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic Survey of Data Mining Technology
Data mining is the revelation of designs and examples in enormous and complex data sets. There are two types of data mining: model structure and example location. Model structure in Data mining is very much like factual demonstrating, albeit new issues emerge on account of the enormous sizes of the Data indexes and the way that Data mining is frequently optional information examination. Example discovery looks for peculiarities or little nearby designs in information, with the tremendous mass of the information being unimportant. For sure, one perspective on numerous large scale information mining exercises is that they basically comprise separating and data reduction.
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